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A solution for Multi-Alignment by Transformation Synchronisation
Bernard, Florian; Thunberg, Johan; Gemmar, Peter et al.
2015In The proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Peer reviewed
 

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Abstract :
[en] The alignment of a set of objects by means of transformations plays an important role in computer vision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used. In practice the iterative methods perform well if the relative transformations between any pair of objects are free of noise. However, if only noisy relative transformations are available (e.g. due to missing data or wrong correspondences) the iterative methods may fail. Based on the observation that the underlying noise-free transformations lie in the null space of a matrix that can directly be obtained from pairwise alignments, this paper presents a novel method for the synchronisation of pairwise transformations such that they are globally consistent. Simulations demonstrate that for a high amount of noise, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Bernard, Florian ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Thunberg, Johan ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Gemmar, Peter
Hertel, Frank ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Husch, Andreas  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Goncalves, Jorge ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
External co-authors :
yes
Language :
English
Title :
A solution for Multi-Alignment by Transformation Synchronisation
Publication date :
2015
Event name :
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Event place :
Boston, United States
Event date :
8-10 June, 2015
Main work title :
The proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Publisher :
IEEE
Peer reviewed :
Peer reviewed
FnR Project :
FNR8864515 - Set Convergence In Nonlinear Multi-agent Systems, 2014 (01/02/2015-31/01/2017) - Johan Thunberg
Commentary :
arXiv:1410.8546
Available on ORBilu :
since 14 April 2015

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